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Simulated evolution and learning : 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014 : proceedings

Author: Grant Dick
Publisher: Cham : Springer, [2014] ©2014
Series: Lecture notes in computer science, 8886.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Database:WorldCat
Summary:
This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine  Read more...
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Details

Genre/Form: Conference papers and proceedings
Congresses
Additional Physical Format: Printed edition:
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Grant Dick
ISBN: 9783319135632 3319135635
OCLC Number: 897803109
Notes: Includes author index.
Description: 1 online resource (xvi, 862 pages) : illustrations.
Contents: Evolutionary optimization --
Evolutionary multi-objective optimization --
Evolutionary machine learning --
Theoretical developments --
Evolutionary feature reduction --
Evolutionary scheduling and combinatorial optimization --
Real world applications and evolutionary image analysis.
Series Title: Lecture notes in computer science, 8886.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Other Titles: SEAL 2014
Responsibility: Grant Dick [and 11 others] (Eds.).

Abstract:

This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.

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